Paper
21 July 2024 Simulation of intelligent allocation model of local cultural and educational resources based on improved particle swarm optimization algorithm
Huanhuan Zhang
Author Affiliations +
Proceedings Volume 13219, Fourth International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2024); 132192G (2024) https://doi.org/10.1117/12.3036523
Event: 4th International Conference on Applied Mathematics, Modelling and Intelligent Computing (CAMMIC 2024), 2024, Kaifeng, China
Abstract
With the continuous development of society, the distribution of cultural and educational resources has become a concern, which is related to the quality of local cultural heritage and education popularization. Traditional resource allocation methods usually have some problems, such as low efficiency, obvious inequality and difficulty in dealing with uncertainty. In order to meet these challenges, this study introduces an improved Particle Swarm Optimization(PSO) algorithm, and constructs an intelligent allocation model of local cultural and educational resources based on adaptive PSO to optimize the allocation of cultural and educational resources. Through the simulation experiment based on real data, this study verifies the effectiveness of the improved PSO algorithm in the allocation of local cultural and educational resources. The results show that the improved PSO algorithm not only improves the efficiency of resource utilization, but also optimizes the resource allocation strategy and reduces the occurrence of inequality. The algorithm also responds to the uncertainty well, which is expected to provide strong support for the intelligent allocation of local cultural and educational resources.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Huanhuan Zhang "Simulation of intelligent allocation model of local cultural and educational resources based on improved particle swarm optimization algorithm", Proc. SPIE 13219, Fourth International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2024), 132192G (21 July 2024); https://doi.org/10.1117/12.3036523
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KEYWORDS
Particle swarm optimization

Particles

Mathematical optimization

Computer simulations

Algorithm development

Cultural studies

Cultural heritage

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